missing heritability - senecio7の日記

Liu X, Li YI & Pritchard JK 2019 Trans effects on gene expression can drive ominigenic inheritance. Cell 177:1022-1034.

we provide a formal model in which genetic contributions to complex traits are partitioned into direct effects from core genes and indirect effects from peripheral genes acting in trans
if the core genes for a trait tend to be co-regulated, then the effects of peripheral variation can be amplified
nearly all of the genetic variance is driven by weak trans effects

most of the missing heritability is due to large numbers of small-effect common variants that are not significant at current sample sizes

between 71% and 100% of 1 megabase (Mb) windows in the genome are estimated to contribute to the heritability of schizophrenia
much of the trait variance is mediated through genes that are not directly involved in the trait in question
these observations appear at odds with conventional ways of understanding the links from genotype to phenotype
much of the progress in classical genetics has come from detailed molecular work to dissect the biological mechanisms of individual mutations

why does such a large portion of the genome contribute to heritability?
why do the lead hits for a typical trait contribute so little to heritability?
what factors determine the effect sizes of SNPs on traits?

it is essential for the field to develop conceptual models for understanding complex trait architecture
the model proposed here is a step in that direction

genes not expressed in relevant cell types do not contribute significantly to heritability
the per-SNP heritability in tissue-specific regulatory elements is only modestly increased relative to SNPs in broadly active regulatory elements, provided that they are active in relevant tissues
the heritability of a typical complex trait is driven by variation in a large number of regulatory elements and genes, spread widely across the genome, and mediated through a wide range of gene functional categories
rare variants are generally not major contributors to the overall phenotypic variance
protein-coding variants are relatively rare in the genome and thus contribute only a small fraction of heritability
the heritability is generally dominated by noncoding variants, especially variants in gene regulatory regions
there is strong enrichment of both cis- and trans-eQTLs among GWAS hits, albeit still a considerable gap in linking all hits to eQTLs

some genes (and their regulatory networks) are functionally proximate to disease risk
these genes tend to produce the biggest signals in common- and rare-variant association studies
they tend to be the most illuminating from the point of view of understanding disease etiology
they are responsible for only a small fraction of the genetic variance in disease risk
the bulk of the heritability is mediated through genes that have a wide variety of functions, many of which have no obvious functional connection to disease
most of the GWAS hits are in noncoding, putatively regulatory regions of the genome
the primary links between genetic variation and complex disease are via gene regulation

the omnigenic model partitions genes into core genes and peripheral genes
core genes can affect disease risk directly
peripheral genes can only affect risk indirectly through trans-regulatory effects on core genes
two key proposals of the omnigenic model are
(1) that most, if not all, genes expressed in trans-relevant cells have the potential to affect core-gene regulation
(2) that for typical traits, nearly all of the heritability is determined by variation near peripheral genes
core genes are the key drivers of disease
it is the cumulative effects of many peripheral gene variants that determine polygenic risk

"omnigenic" has a more precise meaning than the term "polygenic"
polygenic can be used to describe the involvement of anything from tens of loci to every variant in the genome and would include omnigenic as a special case, toward the high end of the polygenic spectrum
we also use the term "omnigenic model" to refer to our specific model of complex trait architecture in which heritability is mainly driven by peripheral genes that trans-regulate core genes
it is also worth distinguishing our model from Fisher's classic infinitesimal model
it does not tell us how many causal variants to expect in practice nor about the molecular mechanisms linking genetic variation to phenotypes

we define a gene as a "core gene" if and only if the gene product (protein, or RNA for a noncoding gene) has a direct effect—not mediated through regulation of another gene—on cellular and organismal processes leading to a change in the expected value of a particular phenotype
all other genes expressed in relevant cell types are considered "peripheral genes" and can only affect the phenotype indirectly through regulatory effects on core genes
genes that are "unexpressed" in trait-relevant tissues are assumed not to contribute to heritability
most peripheral genes make small contributions to heritability
some peripheral genes, such as transcription factors and protein regulators, play important roles because they regulate multiple core genes

Equation 3 illustrates the key factors determining how cis- and trans-eQTL effects on core genes impact complex trait heritability
the first two groups of terms on the right-hand side of this expression depend on the relative importance of cis and trans effects in determining expression heritability of core genes
the third group of terms depends on genetic covariances between pairs of core genes
these genetic covariances must arise from trans effects
there are many more pairs of core genes (nearly M²) than core genes (M)
these terms may dominate the heritability for most traits

most studies are hugely underpowered to detect trans-eQTLs
estimates of trans heritability must rely on statistical methods that aggregate weak signals
the literature is reassuringly consistent across a range of study designs, indicating that around 60%–90% of genetic variance in expression is due to trans-acting variation

trans-eQTLs are notoriously difficult to find in humans
this is partly due to the extra multiple testing burden on trans-eQTLs but is mainly due to the small effect sizes of trans-eQTLs
trans effects are uniformly small compared to cis effects, with only a handful reaching significance
typical genes must have very large numbers of weak trans-eQTLs
this model starts to explain why so much of the genome contributes heritability for typical traits

suppose instead that a considerable fraction of core genes are either co-regulated with shared directions of effects or negatively co-regulated with opposite directions of effects
the sum of covariance terms can dominate the genetic variance for trait Y
covariances are primarily driven by trans effects, co-regulated networks could potentially act as strong amplifiers for trans-acting variants that are shared among core genes in those networks

there has been little work so far on measuring the genetic basis of gene expression correlations
the work to date shows that expression covariance is substantially driven by genetic factors
Goldinger et al. (2013) studied heritability of principal components (PCs) in a dataset of whole-blood gene expression from 335 individuals
they reported a strong genetic component in the lead PCs, with an average heritability of 0.39 for the first 50 PCs
Lukowski et al. (2017) tested for genetic covariance between gene pairs and identified 15,000 gene pairs (0.5% of all gene pairs) with significantly nonzero genetic covariance at 5% false discovery rate
for the 10% of gene pairs with the highest phenotypic correlation, the average genetic correlation is 0.12
this magnitude is potentially large enough to make an important contribution to heritability

if core genes are often co-regulated, with shared directions of effects, as seems likely, then nearly all heritability would be due to trans effects
cis-eQTLs usually have much larger effect sizes than trans-eQTLs
many of the biggest signals in GWASs are cis regulators of core genes
peripheral gene-regulatory variants may become notable hits if they are trans-eQTLs for many core genes with correlated directions of effect
the bulk of trait heritability is driven by a huge number of peripheral variants that are weak trans-eQTLs for core genes

the 57 genome-wide significant loci explain ~20% of the heritability
all variation tagged in current GWASs together explains ~80%
54% of 1 Mb windows in the genome contribute to the heritability of extreme lipid levels
we have clear evidence for the involvement of core genes, yet they contribute only a small fraction of the genetic variance in the trait
much of the remaining variance is due to the combined contributions of many small trans effects being funneled through the core genes